# Gesture Recognition on Multimodal Gesture Dataset (LOPO)

Source: [Gesture Recognition on Multimodal Gesture Dataset (LOPO)](<https://www.sota2.com/research/sota/gesture-recognition-on-multimodal-gesture-dataset-lopo>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-03-06T07:28:24.446Z

Evaluation of Gesture Recognition performance on the Multimodal Gesture Dataset (LOPO), typically measured using F1 Score, Precision, and Recall.

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Gesture Recognition |
| Dataset (including any stated split) | Multimodal Gesture Dataset (LOPO) |
| Metric | F1 Score |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 3 of 3 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [F1 Score](<https://www.sota2.com/research/sota/gesture-recognition-on-multimodal-gesture-dataset-lopo.md?metric=F1%20Score>): Higher is better; unit: PERCENT.

- [Precision](<https://www.sota2.com/research/sota/gesture-recognition-on-multimodal-gesture-dataset-lopo.md?metric=Precision>): Higher is better; unit: PERCENT.

- [Recall](<https://www.sota2.com/research/sota/gesture-recognition-on-multimodal-gesture-dataset-lopo.md?metric=Recall>): Higher is better; unit: PERCENT.

## Recorded results

| Method | F1 Score | Result date | Report paper |
| --- | --- | --- | --- |
| LLR Fusion | 0.9359 | Not recorded | 69a519592d603e6de3e3c6f6 |
| PoseConv3D | 0.9339 | Not recorded | 69a519592d603e6de3e3c6f6 |
| Self-Attention Fusion | 0.9297 | Not recorded | 69a519592d603e6de3e3c6f6 |

### LLR Fusion

F1 Score: 0.9359. Result ID: 69aa80f66dbb7075b953df1e.

[Reporting paper](<https://www.sota2.com/research/paper/69a519592d603e6de3e3c6f6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/69a519592d603e6de3e3c6f6.md>)

Recorded evaluation configuration: {"Input Modality":"sensor"}. This record does not assert independent reproduction.

### PoseConv3D

F1 Score: 0.9339. Result ID: 69aa80f66dbb7075b953df20.

[Reporting paper](<https://www.sota2.com/research/paper/69a519592d603e6de3e3c6f6.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6c321e209131cea32c30.md>)

[Implementation](<https://github.com/kennymckormick/pyskl>)

Recorded evaluation configuration: {"Input Modality":"video"}. This record does not assert independent reproduction.

### Self-Attention Fusion

F1 Score: 0.9297. Result ID: 69aa80f66dbb7075b953df1f.

[Reporting paper](<https://www.sota2.com/research/paper/69a519592d603e6de3e3c6f6.md>)

Recorded evaluation configuration: {"Input Modality":"sensor"}. This record does not assert independent reproduction.

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